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ردیف | عنوان | نوع |
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1 |
Direct Quantum Communications in the Presence of Realistic Noisy Entanglement
ارتباطات کوانتومی مستقیم در حضور درهم تنیدگی پر سر و صدا واقعی-2022 To realize the Quantum Internet, quantum
communications require pre-shared entanglement among quantum nodes. However, both the generation and the distribution
of the maximally-entangled quantum states are inherently contaminated by quantum decoherence. Conventionally, the quantum
decoherence is mitigated by performing the consecutive steps of
quantum entanglement distillation followed by quantum teleportation. However, this conventional approach imposes a long delay.
To circumvent this impediment, we propose a novel quantum
communication scheme relying on realistic noisy pre-shared
entanglement, which eliminates the sequential steps imposing
delay in the standard approach. More precisely, our proposed
scheme can be viewed as a direct quantum communication
scheme capable of improving the quantum bit error ratio (QBER)
of the logical qubits despite relying on realistic noisy pre-shared
entanglement. Our performance analysis shows that the proposed
scheme offers competitive QBER, yield, and goodput compared
to the existing state-of-the-art quantum communication schemes,
despite requiring fewer quantum gates.
Index Terms: Quantum communication | quantum entanglement | quantum error-correction | quantum stabilizer codes | Quantum Internet. |
مقاله انگلیسی |
2 |
Discriminating Quantum States in the Presence of a Deutschian CTC: A Simulation Analysis
حالت های کوانتومی متمایز در حضور CTC Deutschian: یک تحلیل شبیه سازی-2022 In an article published in 2009, Brun et al. proved that in the presence of a “Deutschian”
closed timelike curve, one can map K distinct nonorthogonal states (hereafter, input set) to the standard
orthonormal basis of a K-dimensional state space. To implement this result, the authors proposed a quantum
circuit that includes, among SWAP gates, a fixed set of controlled operators (boxes) and an algorithm for
determining the unitary transformations carried out by such boxes. To our knowledge, what is still missing
to complete the picture is an analysis evaluating the performance of the aforementioned circuit from an
engineering perspective. The objective of this article is, therefore, to address this gap through an in-depth
simulation analysis, which exploits the approach proposed by Brun et al. in 2017. This approach relies on
multiple copies of an input state, multiple iterations of the circuit until a fixed point is (almost) reached. The
performance analysis led us to a number of findings. First, the number of iterations is significantly high even
if the number of states to be discriminated against is small, such as 2 or 3. Second, we envision that such
a number may be shortened as there is plenty of room to improve the unitary transformation acting in the
aforementioned controlled boxes. Third, we also revealed a relationship between the number of iterations
required to get close to the fixed point and the Chernoff limit of the input set used: the higher the Chernoff
bound, the smaller the number of iterations. A comparison, although partial, with another quantum circuit
discriminating the nonorthogonal states, proposed by Nareddula et al. in 2018, is carried out and differences
are highlighted.
INDEX TERMS: Benchmarking and performance characterization | classical simulation of quantum systems. |
مقاله انگلیسی |
3 |
High-accuracy in the classification of butchery cut marks and crocodile tooth marks using machine learning methods and computer vision algorithms
دقت بالا در طبقه بندی علائم برش قصابی و علائم دندان تمساح با استفاده از روش های یادگیری ماشین و الگوریتم های بینایی کامپیوتری-2022 Some researchers using traditional taphonomic criteria (groove shape and presence/absence of microstriations) have cast some doubts about the potential equifinality presented by crocodile tooth marks and
stone tool butchery cut marks. Other researchers have argued that multivariate methods can efficiently
separate both types of marks. Differentiating both taphonomic agents is crucial for determining the earliest evidence of carcass processing by hominins. Here, we use an updated machine learning approach
(discarding artificially bootstrapping the original imbalanced samples) to show that microscopic features
shaped as categorical variables, corresponding to intrinsic properties of mark structure, can accurately
discriminate both types of bone modifications. We also implement new deep-learning methods that
objectively achieve the highest accuracy in differentiating cut marks from crocodile tooth scores (99%
of testing sets). The present study shows that there are precise ways of differentiating both taphonomic
agents, and this invites taphonomists to apply them to controversial paleontological and archaeological
specimens.
keywords: تافونومی | علائم برش | علائم دندان | فراگیری ماشین | یادگیری عمیق | شبکه های عصبی کانولوشنال | قصابی | Taphonomy | Cut marks | Tooth marks | Machine learning | Deep learning | Convolutional neural networks | Butchery |
مقاله انگلیسی |
4 |
General Mixed-State Quantum Data Compression With and Without Entanglement Assistance
فشرده سازی داده های کوانتومی حالت مخلوط عمومی با و بدون کمک درهم تنیدگی-2022 We consider the most general finite-dimensional
quantum mechanical information source, which is given by a
quantum system A that is correlated with a reference system R.
The task is to compress A in such a way as to reproduce the
joint source state ρAR at the decoder with asymptotically high
fidelity. This includes Schumacher’s original quantum source
coding problem of a pure state ensemble and that of a single
pure entangled state, as well as general mixed state ensembles.
Here, we determine the optimal compression rate (in qubits per
source system) in terms of the Koashi-Imoto decomposition of
the source into a classical, a quantum, and a redundant part.
The same decomposition yields the optimal rate in the presence
of unlimited entanglement between compressor and decoder, and
indeed the full region of feasible qubit-ebit rate pairs.
keywords: Quantum information | source coding | entanglement. |
مقاله انگلیسی |
5 |
A systematic review on computer vision-based parking lot management applied on public datasets
مرور سیستماتیک مدیریت پارکینگ مبتنی بر بینایی ماشین اعمال شده بر روی مجموعه داده های عمومی-2022 Computer vision-based parking lot management methods have been extensively researched upon owing to their
flexibility and cost-effectiveness. To evaluate such methods authors often employ publicly available parking lot
image datasets. In this study, we surveyed and compared robust publicly available image datasets specifically
crafted to test computer vision-based methods for parking lot management approaches and consequently
present a systematic and comprehensive review of existing works that employ such datasets. The literature
review identified relevant gaps that require further research, such as the requirement of dataset-independent
approaches and methods suitable for autonomous detection of position of parking spaces. In addition, we have
noticed that several important factors such as the presence of the same cars across consecutive images, have
been neglected in most studies, thereby rendering unrealistic assessment protocols. Furthermore, the analysis
of the datasets also revealed that certain features that should be present when developing new benchmarks,
such as the availability of video sequences and images taken in more diverse conditions, including nighttime
and snow, have not been incorporated.
keywords: Parking lot | Dataset | Benchmark | Machine learning | Image processing |
مقاله انگلیسی |
6 |
A radiological image analysis framework for early screening of the COVID-19 infection: A computer vision-based approach
چارچوب تجزیه و تحلیل تصویر رادیولوژیکی برای غربالگری اولیه عفونت COVID-19: یک رویکرد مبتنی بر بینایی کامپیوتری-2022 Due to the absence of any specialized drugs, the novel coronavirus disease 2019 or COVID-19 is
one of the biggest threats to mankind Although the RT-PCR test is the gold standard to confirm
the presence of this virus, some radiological investigations find some important features from the
CT scans of the chest region, which are helpful to identify the suspected COVID-19 patients. This
article proposes a novel fuzzy superpixel-based unsupervised clustering approach that can be useful
to automatically process the CT scan images without any manual annotation and helpful in the easy
interpretation. The proposed approach is based on artificial cell swarm optimization and will be
known as the SUFACSO (SUperpixel based Fuzzy Artificial Cell Swarm Optimization) and implemented
in the Matlab environment. The proposed approach uses a novel superpixel computation method
which is helpful to effectively represent the pixel intensity information which is beneficial for the
optimization process. Superpixels are further clustered using the proposed fuzzy artificial cell swarm
optimization approach. So, a twofold contribution can be observed in this work which is helpful
to quickly diagnose the patients in an unsupervised manner so that, the suspected persons can be
isolated at an early phase to combat the spread of the COVID-19 virus and it is the major clinical
impact of this work. Both qualitative and quantitative experimental results show the effectiveness of
the proposed approach and also establish it as an effective computer-aided tool to fight against the
COVID-19 virus. Four well-known cluster validity measures Davies–Bouldin, Dunn, Xie–Beni, and β
index are used to quantify the segmented results and it is observed that the proposed approach not
only performs well but also outperforms some of the standard approaches. On average, the proposed
approach achieves 1.709792, 1.473037, 1.752433, 1.709912 values of the Xie–Beni index for 3, 5,7, and
9 clusters respectively and these values are significantly lesser compared to the other state-of-the-art
approaches. The general direction of this research is worthwhile pursuing leading, eventually, to a
contribution to the community.
keywords: کووید-۱۹ | تفسیر تصویر رادیولوژیکی | سوپرپیکسل | سیستم فازی نوع 2 | بهینه سازی ازدحام سلول های مصنوعی | COVID-19 | Radiological image interpretation | Superpixel | Type 2 fuzzy system | Artificial cell swarm optimization |
مقاله انگلیسی |
7 |
Face mask recogniser using image processing and computer vision approach
تشخیص ماسک صورت با استفاده از پردازش تصویر و رویکرد بینایی کامپیوتری-2022 The world saw a health crisis with the onset of the COVID-19 virus outbreak. The mask has been identified as
the most efficient way to prevent the spread of virus [1]. This has driven the necessity for a face mask recogniser
that not only detects the presence of a mask but also gives the accuracy to which a person is wearing the face
mask. Also, the face mask should be recognised in all angles as well. The goal of this study is to create a new
and improved real time face mask recogniser using image processing and computer vision approach. A Kaggle
dataset which consisted of images with and without masks was used. For the purpose of this study a pre-trained
convolutional neural network Mobile Net V2 was used. The performance of the given model was assessed. The
model presented in this paper can detect the face mask with 98% precision. This Face mask recogniser can effi-
ciently detect the face mask in side wise direction which makes it more useful. A comparison of the performance
metrics of the existing algorithms is also presented. Now with the spread of the infectious variant OMICRON, it
is necessary to implement such a robust face mask recogniser which can help control the spread. keywords: Computer Vision | Convolutional Neural Network | Face mask detection | Image processing | Kaggle dataset | Keras | MobileNetV2 | Open CV | Tensor-Flow |
مقاله انگلیسی |
8 |
Pauli Error Propagation-Based Gate Rescheduling for Quantum Circuit Error Mitigation
برنامه ریزی مجدد گیت مبتنی بر انتشار خطا پاولی برای کاهش خطای مدار کوانتومی-2022 Noisy intermediate-scale quantum algorithms, which run on noisy quantum computers, should
be carefully designed to boost the output state fidelity. While several compilation approaches have been
proposed to minimize circuit errors, they often omit the detailed circuit structure information that does
not affect the circuit depth or the gate count. In the presence of spatial variation in the error rate of the
quantum gates, adjusting the circuit structure can play a major role in mitigating errors. In this article, we
exploit the freedom of gate reordering based on the commutation rules to show the impact of gate error
propagation paths on the output state fidelity of the quantum circuit, propose advanced predictive techniques
to project the success rate of the circuit, and develop a new compilation phase postquantum circuit mapping
to improve its reliability. Our proposed approaches have been validated using a variety of quantum circuits
with different success metrics, which are executed on IBM quantum computers. Our results show that
rescheduling quantum gates based on their error propagation paths can significantly improve the fidelity
of the quantum circuit in the presence of variable gate error rates.
INDEX TERMS: Commutation rules | error propagation | gate rescheduling | noisy intermediate-scale quantum (NISQ) computer | Pauli errors | quantum circuit | quantum circuit mapping | reliability. |
مقاله انگلیسی |
9 |
تجزیه و تحلیل پوششی داده مبتنی بر نسبت: یک رویکرد تعاملی برای شناسایی معیار
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 14 - تعداد صفحات فایل doc فارسی: 40 در دنیای واقعی ما با موارد زیادی مواجه هستیم که در آن نسبت داده های ورودی/خروجی برای مدیران بسیار مهم است، بنابراین در این رابطه نمی توان از مدل های سنتی تحلیل پوششی داده (DEA) برای ارزیابی کارایی واحدهای تصمیم گیری (DMU) استفاده کرد، و باید از مدل های DEA بر اساس داده های نسبت بهره برد. برای بدست آوردن معیار مربوطه برای هر واحد تصمیمگیری ناکارآمد، باید ورودیها و خروجیها را به ترتیب کاهش و افزایش دهیم و به یک پیشبینی واحد و منسجم تصمیمگیرنده در مرز کارایی برسیم. در این مقاله ما یک مدل برنامهریزی خطی چندهدفه (MOLP) (multi-objective linear programming) را برای ارزیابی کارایی بر اساس تعریف مجموعه امکان تولید در حضور دادههای نسبت و به دست آوردن معیار مربوطه برای هر واحد تصمیمگیری DMU ارائه میکنیم. ما از روش تعاملی زایونتس و والنیوس (Z-W) برای حل مدل MOLP ارائه شده استفاده میکنیم. با استفاده از تنظیم هدف توسط مدیر از بین راه حل های حاصل از مسئله MOLP، بهترین راه حل را با توجه به ترجیحات مدیران به عنوان معیار انتخاب می کنیم و در پایان نتایج تحقیق را ارائه می کنیم.
واژگان کلیدی: کارایی | DEA-R | معیار | برنامه ریزی چند هدفه | روش تعاملی |
مقاله ترجمه شده |
10 |
Quantum Error Mitigation Relying on Permutation Filtering
کاهش خطای کوانتومی با تکیه بر فیلتر جایگشت-2022 Quantum error mitigation (QEM) is a class of
promising techniques capable of reducing the computational
error of variational quantum algorithms tailored for current
noisy intermediate-scale quantum computers. The recently pro-
posed permutation-based methods are practically attractive,
since they do not rely on any a priori information concerning
the quantum channels. In this treatise, we propose a general
framework termed as permutation filters, which includes the
existing permutation-based methods as special cases. In particular, we show that
the proposed filter design algorithm
always converge to the global optimum, and that the optimal
filters can provide substantial improvements over the existing
permutation-based methods in the presence of narrowband
quantum noise, corresponding to large-depth, high-error-rate
quantum circuits. keywords: Quantum error mitigation | permutation filtering | permutation symmetry | variational quantum algorithms. |
مقاله انگلیسی |